Thursday, July 18, 2013

Matlab Tip: Changing line-width of all the lines via commandline

Get the handle to the line using:
hline = findobj(gcf, 'type', 'line');
Then  you can change some property for all the line objects:
set(hline,'LineWidth',3)
or just for some of them :
set(hline(1),'LineWidth',3)
set(hline(2:3),'LineStyle',':')
idx = [4 5];
set(hline(idx),'Marker','*')
This is not an original post. Here is the original post

Thursday, April 11, 2013

Surviving the PhD program

As I am nearing the end of the longest phase of my academic life, I wanted to put together all resources that are useful to keep one going during the frustrating times of a PhD program. I truly believe that keeping a positive emotional state and using our energies in the right direction is the key to getting through the program. I am grateful to have a good support of friends and family but the internet is a great place to seek support in times of trouble. Here are some of the most useful links that I found.

  • Dissertation Writers Toolkit : A great resource for those who are procrastinating on writing. This webpage also contains tons of other helpful material, like balanced-life chart, tools on staying organized, positive affirmations on writing and so on.
  • Life is easier when you can laugh at yourself. Here are some daily affirmations for doctoral students. But I stayed away from PhD comics as much as I could.
  • The Thesis Whisperer is another useful blog, that helped me realize I was not alone in some of my struggles. In fact my struggles are perfectly normal for a PhD student.
  • Here are some productivity tricks for graduate students that I found useful. In fact, following one of the suggestions from this page, I purchased multiple chargers for my laptop so I could save time on getting started with my day.
  • The 3-month thesis is also a good resource for thesis writing

Wednesday, April 3, 2013

Trailing Slash in rsync command

Just making a quick reference to the rysnc manual in order to synchronize directories

The command used to copy folders is as follows:
 
rsync -avz foo:src/bar /data/tmp
 
This command copies the directory bar in /data/tmp .. 
meaning at the end of this command, you will have /data/tmp/bar folder
 
 
If you just want to sync the folders then use the trailing slash like this
 
rsync -avz foo:src/bar/ /data/tmp 

Now only the contents of bar will be copied into /data/tmp folder;
 you will not find a folder called bar in /data/tmp

Wednesday, March 27, 2013

The caveats of using tar to create archives

So I recently created a bunch of tar files that had a long path name when unzipped. This long path name was the absolute path on the computer where the tar files were created. For example

tar c /home/shivani/testfile.txt
will create a tar that when unzipped will create /home/shivani/testfile.txt in the folder where you untar the file. 

In order to ensure this does not happen use the -C option, that cds into the directory /home/shivani and then creates the tar. 

This caveat was found on this webapge

Tuesday, March 12, 2013

Review of Available Implementations of the Latent Dirichlet Allocation

A part of my dissertation is based on the Latent Dirichlet Allocation Model and I have extensively searched for played with various LDA implementations.

Gibbs Sampling implementation of LDA in C++
The input format is basically a single text file that contains one line for each document. Each line contains the actual terms. I found this input format to be bulky. The code itself is very clean and easy to understand. Gibbs Sampling by itself is a little slow and nothing can be done about it.

Gibbs Sampling Implementation of LDA in Java
Written by the same folks who wrote the c++ implementation. Leaving the programming language aside everything else is kept same.

Variational Inference of LDA in Matlab and C
This is easy to use code that uses the input format as that of  SVMLight software, which is basically a text file with each line containing a sequence of tuples of the format : where the feature_id is the word_id based on a dictionary and count is the number of times it appears in the corpus. Implementation wise, I have one comment though. I was hoping that the algorithm would include estimation of the \eta parameter, the smoothing parameter on \beta.

MALLET toolbox
This is written in Java and uses plain text or SVM light format as input. It implements the Gibbs Sampling for LDA and allows for optimization of the hyper parameters \alpha and \eta after burn-in iterations. This allows us to exercise greater control over the impact of topics on the entire collection. Given that LDA itself is slow and that for estimation of hyper parameters we need to wait for burn-in number of iterations, I feel discouraged to use this tool.

Hybrid approach to LDA inference
This approach apparently uses both Variational and Gibbs Sampling based approach to learn the parameters. The author also presents a vanilla LDA implementation.

I will keep updating this post as and when I find more useful stuff.